{"title":"Performance Bounds for Cooperative Simultaneous Localization and Mapping (C-SLAM)","authors":"Anastasios I. Mourikis, S. Roumeliotis","doi":"10.15607/RSS.2005.I.010","DOIUrl":null,"url":null,"abstract":"In this Technical Report we study the time evolution of the position estimates’ covariance in Cooperative Simultaneous Localization and Mapping (C-SLAM), and obtain analytical upper boundsfor the positioning uncertainty. The derived bounds provide descriptions of the asymptotic positioning performance of a team of robots in a mapping task, as a function of the characteristics of the proprioceptive and exteroceptive sensors of the robots, and of the graph of relative position measurements recorded by the robots. A study of the properties of the Riccati recursion which describes the propagation of uncertainty through time, yields (i) the guaranteed accuracyfor a robot team in a given C-SLAM application, as well as (ii) the maximum expected steady state uncertainty of the robots and landmarks, when the spatial distribution of features in the environment can be modeled by a known distribution.","PeriodicalId":87357,"journal":{"name":"Robotics science and systems : online proceedings","volume":"373 1","pages":"73-80"},"PeriodicalIF":0.0000,"publicationDate":"2005-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"37","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Robotics science and systems : online proceedings","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.15607/RSS.2005.I.010","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 37
Abstract
In this Technical Report we study the time evolution of the position estimates’ covariance in Cooperative Simultaneous Localization and Mapping (C-SLAM), and obtain analytical upper boundsfor the positioning uncertainty. The derived bounds provide descriptions of the asymptotic positioning performance of a team of robots in a mapping task, as a function of the characteristics of the proprioceptive and exteroceptive sensors of the robots, and of the graph of relative position measurements recorded by the robots. A study of the properties of the Riccati recursion which describes the propagation of uncertainty through time, yields (i) the guaranteed accuracyfor a robot team in a given C-SLAM application, as well as (ii) the maximum expected steady state uncertainty of the robots and landmarks, when the spatial distribution of features in the environment can be modeled by a known distribution.